Overview

Brought to you by YData

Dataset statistics

Number of variables16
Number of observations50000
Missing cells3270
Missing cells (%)0.4%
Total size in memory6.5 MiB
Average record size in memory136.0 B

Variable types

Numeric6
Text10

Alerts

post_code has 1150 (2.3%) missing valuesMissing
post_code_prefix has 1150 (2.3%) missing valuesMissing
country has 750 (1.5%) missing valuesMissing
venue_server_id is highly skewed (γ1 = 21.7836194)Skewed
performance_reserved has 47703 (95.4%) zerosZeros

Reproduction

Analysis started2025-11-02 20:39:03.379737
Analysis finished2025-11-02 20:39:04.851086
Duration1.47 second
Software versionydata-profiling vv4.17.0
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

Distinct40463
Distinct (%)80.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean775855.542
Minimum4
Maximum1233429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.2 KiB
2025-11-02T20:39:04.972619image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile56126.6
Q1467353
median894561.5
Q31114738.25
95-th percentile1202578.05
Maximum1233429
Range1233425
Interquartile range (IQR)647385.25

Descriptive statistics

Standard deviation386092.5379
Coefficient of variation (CV)0.4976345685
Kurtosis-1.018343925
Mean775855.542
Median Absolute Deviation (MAD)255849
Skewness-0.6096614659
Sum3.87927771 × 1010
Variance1.490674478 × 1011
MonotonicityNot monotonic
2025-11-02T20:39:05.136839image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36893752
 
0.1%
615
 
< 0.1%
30567714
 
< 0.1%
1593112
 
< 0.1%
36349812
 
< 0.1%
9692511
 
< 0.1%
164311
 
< 0.1%
90789310
 
< 0.1%
1635210
 
< 0.1%
59717610
 
< 0.1%
Other values (40453)49843
99.7%
ValueCountFrequency (%)
42
 
< 0.1%
615
< 0.1%
151
 
< 0.1%
202
 
< 0.1%
241
 
< 0.1%
ValueCountFrequency (%)
12334292
< 0.1%
12311753
< 0.1%
12311081
 
< 0.1%
12311001
 
< 0.1%
12310951
 
< 0.1%

post_code
Text

Missing 

Distinct32225
Distinct (%)66.0%
Missing1150
Missing (%)2.3%
Memory size781.2 KiB
2025-11-02T20:39:05.657355image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length15
Median length14
Mean length7.162108495
Min length1

Characters and Unicode

Total characters349869
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22907 ?
Unique (%)46.9%

Sample

1st rowPL5 3UB
2nd row33100
3rd rowEH21 7BS
4th rowDD11 4BJ
5th rowHP5 1EG
ValueCountFrequency (%)
eh41280
 
1.4%
eh61202
 
1.3%
eh101121
 
1.2%
eh31078
 
1.2%
eh71030
 
1.1%
eh12881
 
0.9%
eh9860
 
0.9%
eh11839
 
0.9%
eh8663
 
0.7%
eh14585
 
0.6%
Other values (9051)83797
89.8%
2025-11-02T20:39:06.299498image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44486
 
12.7%
128801
 
8.2%
E23965
 
6.8%
H22067
 
6.3%
216807
 
4.8%
413013
 
3.7%
312596
 
3.6%
511744
 
3.4%
611236
 
3.2%
010310
 
2.9%
Other values (62)154844
44.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)349869
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
44486
 
12.7%
128801
 
8.2%
E23965
 
6.8%
H22067
 
6.3%
216807
 
4.8%
413013
 
3.7%
312596
 
3.6%
511744
 
3.4%
611236
 
3.2%
010310
 
2.9%
Other values (62)154844
44.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)349869
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
44486
 
12.7%
128801
 
8.2%
E23965
 
6.8%
H22067
 
6.3%
216807
 
4.8%
413013
 
3.7%
312596
 
3.6%
511744
 
3.4%
611236
 
3.2%
010310
 
2.9%
Other values (62)154844
44.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)349869
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
44486
 
12.7%
128801
 
8.2%
E23965
 
6.8%
H22067
 
6.3%
216807
 
4.8%
413013
 
3.7%
312596
 
3.6%
511744
 
3.4%
611236
 
3.2%
010310
 
2.9%
Other values (62)154844
44.3%

post_code_prefix
Text

Missing 

Distinct9189
Distinct (%)18.8%
Missing1150
Missing (%)2.3%
Memory size781.2 KiB
2025-11-02T20:39:06.795764image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length10
Median length5
Mean length5.338423746
Min length1

Characters and Unicode

Total characters260782
Distinct characters71
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3660 ?
Unique (%)7.5%

Sample

1st rowPL5 3
2nd row33100
3rd rowEH21 7
4th rowDD11 4
5th rowHP5 1
ValueCountFrequency (%)
55296
 
5.7%
15232
 
5.6%
24749
 
5.1%
64616
 
4.9%
44569
 
4.9%
84381
 
4.7%
94347
 
4.7%
34165
 
4.5%
74075
 
4.4%
02903
 
3.1%
Other values (5163)48987
52.5%
2025-11-02T20:39:07.420473image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44470
17.1%
128754
 
11.0%
E18038
 
6.9%
216750
 
6.4%
H16314
 
6.3%
412962
 
5.0%
312530
 
4.8%
511689
 
4.5%
611192
 
4.3%
010257
 
3.9%
Other values (61)77826
29.8%

Most occurring categories

ValueCountFrequency (%)
(unknown)260782
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
44470
17.1%
128754
 
11.0%
E18038
 
6.9%
216750
 
6.4%
H16314
 
6.3%
412962
 
5.0%
312530
 
4.8%
511689
 
4.5%
611192
 
4.3%
010257
 
3.9%
Other values (61)77826
29.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown)260782
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
44470
17.1%
128754
 
11.0%
E18038
 
6.9%
216750
 
6.4%
H16314
 
6.3%
412962
 
5.0%
312530
 
4.8%
511689
 
4.5%
611192
 
4.3%
010257
 
3.9%
Other values (61)77826
29.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown)260782
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
44470
17.1%
128754
 
11.0%
E18038
 
6.9%
216750
 
6.4%
H16314
 
6.3%
412962
 
5.0%
312530
 
4.8%
511689
 
4.5%
611192
 
4.3%
010257
 
3.9%
Other values (61)77826
29.8%

country
Text

Missing 

Distinct92
Distinct (%)0.2%
Missing750
Missing (%)1.5%
Memory size781.2 KiB
2025-11-02T20:39:07.693013image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length38
Median length14
Mean length13.64186802
Min length4

Characters and Unicode

Total characters671862
Distinct characters53
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)< 0.1%

Sample

1st rowUnited Kingdom
2nd rowFinland
3rd rowUnited Kingdom
4th rowUnited Kingdom
5th rowUnited Kingdom
ValueCountFrequency (%)
united46693
48.5%
kingdom44786
46.6%
states1868
 
1.9%
australia415
 
0.4%
ireland340
 
0.4%
germany235
 
0.2%
canada211
 
0.2%
netherlands151
 
0.2%
france118
 
0.1%
norway102
 
0.1%
Other values (99)1274
 
1.3%
2025-11-02T20:39:08.089894image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n93200
13.9%
d92520
13.8%
i92438
13.8%
t51331
7.6%
e50293
7.5%
46943
7.0%
U46699
7.0%
m45179
6.7%
o45123
6.7%
g44957
6.7%
Other values (43)63179
9.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)671862
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n93200
13.9%
d92520
13.8%
i92438
13.8%
t51331
7.6%
e50293
7.5%
46943
7.0%
U46699
7.0%
m45179
6.7%
o45123
6.7%
g44957
6.7%
Other values (43)63179
9.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)671862
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n93200
13.9%
d92520
13.8%
i92438
13.8%
t51331
7.6%
e50293
7.5%
46943
7.0%
U46699
7.0%
m45179
6.7%
o45123
6.7%
g44957
6.7%
Other values (43)63179
9.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)671862
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n93200
13.9%
d92520
13.8%
i92438
13.8%
t51331
7.6%
e50293
7.5%
46943
7.0%
U46699
7.0%
m45179
6.7%
o45123
6.7%
g44957
6.7%
Other values (43)63179
9.4%
Distinct46908
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size781.2 KiB
2025-11-02T20:39:08.381501image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters550000
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44411 ?
Unique (%)88.8%

Sample

1st row180:2755036
2nd row180:2971362
3rd row180:3222183
4th row180:3055761
5th row180:2835129
ValueCountFrequency (%)
180:28307067
 
< 0.1%
180:28174746
 
< 0.1%
180:27364766
 
< 0.1%
180:27170386
 
< 0.1%
180:28526516
 
< 0.1%
180:27273646
 
< 0.1%
180:27149636
 
< 0.1%
180:27231216
 
< 0.1%
180:27211716
 
< 0.1%
180:27155696
 
< 0.1%
Other values (46898)49939
99.9%
2025-11-02T20:39:08.793406image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
883223
15.1%
182490
15.0%
082158
14.9%
260121
10.9%
:50000
9.1%
348280
8.8%
735937
6.5%
932306
 
5.9%
626001
 
4.7%
425005
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown)550000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
883223
15.1%
182490
15.0%
082158
14.9%
260121
10.9%
:50000
9.1%
348280
8.8%
735937
6.5%
932306
 
5.9%
626001
 
4.7%
425005
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown)550000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
883223
15.1%
182490
15.0%
082158
14.9%
260121
10.9%
:50000
9.1%
348280
8.8%
735937
6.5%
932306
 
5.9%
626001
 
4.7%
425005
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown)550000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
883223
15.1%
182490
15.0%
082158
14.9%
260121
10.9%
:50000
9.1%
348280
8.8%
735937
6.5%
932306
 
5.9%
626001
 
4.7%
425005
 
4.5%

no_of_tickets
Real number (ℝ)

Distinct34
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.25654
Minimum1
Maximum80
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.2 KiB
2025-11-02T20:39:08.925563image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q32
95-th percentile4
Maximum80
Range79
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.503706238
Coefficient of variation (CV)0.666376948
Kurtosis227.2034188
Mean2.25654
Median Absolute Deviation (MAD)0
Skewness8.010635296
Sum112827
Variance2.261132451
MonotonicityNot monotonic
2025-11-02T20:39:09.060009image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
225717
51.4%
112459
24.9%
34842
 
9.7%
44521
 
9.0%
51044
 
2.1%
6719
 
1.4%
7219
 
0.4%
8186
 
0.4%
1080
 
0.2%
961
 
0.1%
Other values (24)152
 
0.3%
ValueCountFrequency (%)
112459
24.9%
225717
51.4%
34842
 
9.7%
44521
 
9.0%
51044
 
2.1%
ValueCountFrequency (%)
801
< 0.1%
511
< 0.1%
501
< 0.1%
411
< 0.1%
331
< 0.1%
Distinct3945
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size781.2 KiB
2025-11-02T20:39:09.570231image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters800000
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique528 ?
Unique (%)1.1%

Sample

1st row05/08/2019 13:00
2nd row07/08/2019 16:30
3rd row22/08/2019 19:00
4th row12/08/2019 16:30
5th row03/08/2019 23:40
ValueCountFrequency (%)
17/08/20192958
 
3.0%
24/08/20192807
 
2.8%
10/08/20192680
 
2.7%
16/08/20192508
 
2.5%
21:002507
 
2.5%
23/08/20192322
 
2.3%
06/08/20192205
 
2.2%
18/08/20192180
 
2.2%
15/08/20192162
 
2.2%
05/08/20192082
 
2.1%
Other values (202)75589
75.6%
2025-11-02T20:39:10.214695image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0182867
22.9%
1125365
15.7%
/100000
12.5%
291187
11.4%
960025
 
7.5%
858582
 
7.3%
50000
 
6.2%
:50000
 
6.2%
325422
 
3.2%
523549
 
2.9%
Other values (3)33003
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)800000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0182867
22.9%
1125365
15.7%
/100000
12.5%
291187
11.4%
960025
 
7.5%
858582
 
7.3%
50000
 
6.2%
:50000
 
6.2%
325422
 
3.2%
523549
 
2.9%
Other values (3)33003
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)800000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0182867
22.9%
1125365
15.7%
/100000
12.5%
291187
11.4%
960025
 
7.5%
858582
 
7.3%
50000
 
6.2%
:50000
 
6.2%
325422
 
3.2%
523549
 
2.9%
Other values (3)33003
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)800000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0182867
22.9%
1125365
15.7%
/100000
12.5%
291187
11.4%
960025
 
7.5%
858582
 
7.3%
50000
 
6.2%
:50000
 
6.2%
325422
 
3.2%
523549
 
2.9%
Other values (3)33003
 
4.1%

event
Text

Distinct2919
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size781.2 KiB
2025-11-02T20:39:10.630810image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length205
Median length81
Mean length25.78152
Min length1

Characters and Unicode

Total characters1289076
Distinct characters102
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique361 ?
Unique (%)0.7%

Sample

1st rowSplash Test Dummies
2nd rowAdventures of the Improvised Sherlock Holmes
3rd rowKai Samra: Underclass
4th rowThe Black Blues Brothers
5th rowMassaoke Mixtape
ValueCountFrequency (%)
the12935
 
6.0%
of4930
 
2.3%
and3619
 
1.7%
a2919
 
1.3%
in2321
 
1.1%
musical1858
 
0.9%
to1749
 
0.8%
live1654
 
0.8%
1652
 
0.8%
show1469
 
0.7%
Other values (5040)181393
83.8%
2025-11-02T20:39:11.237216image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
167656
 
13.0%
e110542
 
8.6%
o76006
 
5.9%
a73951
 
5.7%
n67939
 
5.3%
i66207
 
5.1%
r65333
 
5.1%
t57018
 
4.4%
s56264
 
4.4%
l44668
 
3.5%
Other values (92)503492
39.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)1289076
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
167656
 
13.0%
e110542
 
8.6%
o76006
 
5.9%
a73951
 
5.7%
n67939
 
5.3%
i66207
 
5.1%
r65333
 
5.1%
t57018
 
4.4%
s56264
 
4.4%
l44668
 
3.5%
Other values (92)503492
39.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1289076
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
167656
 
13.0%
e110542
 
8.6%
o76006
 
5.9%
a73951
 
5.7%
n67939
 
5.3%
i66207
 
5.1%
r65333
 
5.1%
t57018
 
4.4%
s56264
 
4.4%
l44668
 
3.5%
Other values (92)503492
39.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1289076
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
167656
 
13.0%
e110542
 
8.6%
o76006
 
5.9%
a73951
 
5.7%
n67939
 
5.3%
i66207
 
5.1%
r65333
 
5.1%
t57018
 
4.4%
s56264
 
4.4%
l44668
 
3.5%
Other values (92)503492
39.1%
Distinct10
Distinct (%)< 0.1%
Missing220
Missing (%)0.4%
Memory size781.2 KiB
2025-11-02T20:39:11.412243image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length33
Median length19
Mean length10.01275613
Min length5

Characters and Unicode

Total characters498435
Distinct characters33
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowChildren's Shows
2nd rowComedy
3rd rowComedy
4th rowDance Physical Theatre and Circus
5th rowMusic
ValueCountFrequency (%)
comedy22126
28.4%
theatre16492
21.2%
and8438
 
10.8%
dance4278
 
5.5%
physical4278
 
5.5%
circus4278
 
5.5%
music3986
 
5.1%
variety2136
 
2.7%
cabaret2136
 
2.7%
children's2058
 
2.6%
Other values (7)7680
 
9.9%
2025-11-02T20:39:11.698128image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e68639
13.8%
a43942
 
8.8%
d33238
 
6.7%
C30598
 
6.1%
r29740
 
6.0%
y28540
 
5.7%
28106
 
5.6%
o25477
 
5.1%
h24947
 
5.0%
m22126
 
4.4%
Other values (23)163082
32.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)498435
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e68639
13.8%
a43942
 
8.8%
d33238
 
6.7%
C30598
 
6.1%
r29740
 
6.0%
y28540
 
5.7%
28106
 
5.6%
o25477
 
5.1%
h24947
 
5.0%
m22126
 
4.4%
Other values (23)163082
32.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)498435
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e68639
13.8%
a43942
 
8.8%
d33238
 
6.7%
C30598
 
6.1%
r29740
 
6.0%
y28540
 
5.7%
28106
 
5.6%
o25477
 
5.1%
h24947
 
5.0%
m22126
 
4.4%
Other values (23)163082
32.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)498435
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e68639
13.8%
a43942
 
8.8%
d33238
 
6.7%
C30598
 
6.1%
r29740
 
6.0%
y28540
 
5.7%
28106
 
5.6%
o25477
 
5.1%
h24947
 
5.0%
m22126
 
4.4%
Other values (23)163082
32.7%

performance_reserved
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04594
Minimum0
Maximum1
Zeros47703
Zeros (%)95.4%
Negative0
Negative (%)0.0%
Memory size781.2 KiB
2025-11-02T20:39:11.793128image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2093570945
Coefficient of variation (CV)4.557185339
Kurtosis16.81747666
Mean0.04594
Median Absolute Deviation (MAD)0
Skewness4.337834018
Sum2297
Variance0.04383039301
MonotonicityNot monotonic
2025-11-02T20:39:11.884901image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
047703
95.4%
12297
 
4.6%
ValueCountFrequency (%)
047703
95.4%
12297
 
4.6%
ValueCountFrequency (%)
12297
 
4.6%
047703
95.4%

venue_server_id
Real number (ℝ)

Skewed 

Distinct23
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.92188
Minimum1
Maximum6914
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.2 KiB
2025-11-02T20:39:11.984624image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median26
Q361
95-th percentile150
Maximum6914
Range6913
Interquartile range (IQR)58

Descriptive statistics

Standard deviation279.556385
Coefficient of variation (CV)5.090073119
Kurtosis526.7163413
Mean54.92188
Median Absolute Deviation (MAD)23
Skewness21.7836194
Sum2746094
Variance78151.77241
MonotonicityNot monotonic
2025-11-02T20:39:12.107098image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
310103
20.2%
3310073
20.1%
19427
18.9%
616684
13.4%
144431
8.9%
262172
 
4.3%
1321389
 
2.8%
881381
 
2.8%
231721
 
1.4%
34595
 
1.2%
Other values (13)3024
 
6.0%
ValueCountFrequency (%)
19427
18.9%
310103
20.2%
144431
8.9%
18290
 
0.6%
22246
 
0.5%
ValueCountFrequency (%)
691473
 
0.1%
913183
 
0.4%
671279
0.6%
515557
1.1%
3176
 
< 0.1%

venue_id
Real number (ℝ)

Distinct170
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.20138
Minimum1
Maximum1136
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.2 KiB
2025-11-02T20:39:12.250055image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median12
Q324
95-th percentile792
Maximum1136
Range1135
Interquartile range (IQR)23

Descriptive statistics

Standard deviation233.6818017
Coefficient of variation (CV)2.332121591
Kurtosis7.39423592
Mean100.20138
Median Absolute Deviation (MAD)11
Skewness2.853681271
Sum5010069
Variance54607.18445
MonotonicityNot monotonic
2025-11-02T20:39:12.403907image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
116335
32.7%
174370
 
8.7%
163477
 
7.0%
242387
 
4.8%
21902
 
3.8%
181802
 
3.6%
191740
 
3.5%
51645
 
3.3%
261400
 
2.8%
41229
 
2.5%
Other values (160)13713
27.4%
ValueCountFrequency (%)
116335
32.7%
21902
 
3.8%
31139
 
2.3%
41229
 
2.5%
51645
 
3.3%
ValueCountFrequency (%)
11363
< 0.1%
11236
< 0.1%
11201
 
< 0.1%
11192
 
< 0.1%
11175
< 0.1%

venue
Text

Distinct214
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size781.2 KiB
2025-11-02T20:39:12.827952image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length59
Median length42
Mean length21.73908
Min length4

Characters and Unicode

Total characters1086954
Distinct characters68
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)< 0.1%

Sample

1st rowUnderbelly's Circus Hub on the Meadows
2nd rowJust The Tonic at the Caves
3rd rowPleasance Courtyard
4th rowAssembly Rooms
5th rowAssembly George Square Gardens
ValueCountFrequency (%)
square10087
 
6.4%
pleasance10073
 
6.4%
assembly10072
 
6.4%
the7968
 
5.1%
courtyard7130
 
4.5%
george6423
 
4.1%
underbelly5759
 
3.7%
5367
 
3.4%
gilded4431
 
2.8%
balloon4431
 
2.8%
Other values (363)86009
54.5%
2025-11-02T20:39:13.447245image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e133498
 
12.3%
109645
 
10.1%
a78118
 
7.2%
l68311
 
6.3%
r65431
 
6.0%
o61398
 
5.6%
s60886
 
5.6%
t45814
 
4.2%
n41445
 
3.8%
d37371
 
3.4%
Other values (58)385037
35.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)1086954
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e133498
 
12.3%
109645
 
10.1%
a78118
 
7.2%
l68311
 
6.3%
r65431
 
6.0%
o61398
 
5.6%
s60886
 
5.6%
t45814
 
4.2%
n41445
 
3.8%
d37371
 
3.4%
Other values (58)385037
35.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1086954
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e133498
 
12.3%
109645
 
10.1%
a78118
 
7.2%
l68311
 
6.3%
r65431
 
6.0%
o61398
 
5.6%
s60886
 
5.6%
t45814
 
4.2%
n41445
 
3.8%
d37371
 
3.4%
Other values (58)385037
35.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1086954
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e133498
 
12.3%
109645
 
10.1%
a78118
 
7.2%
l68311
 
6.3%
r65431
 
6.0%
o61398
 
5.6%
s60886
 
5.6%
t45814
 
4.2%
n41445
 
3.8%
d37371
 
3.4%
Other values (58)385037
35.4%

subvenue_id
Real number (ℝ)

Distinct270
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean192.11278
Minimum1
Maximum1723
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.2 KiB
2025-11-02T20:39:13.598261image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q17
median37
Q382
95-th percentile1366
Maximum1723
Range1722
Interquartile range (IQR)75

Descriptive statistics

Standard deviation401.7673584
Coefficient of variation (CV)2.091309898
Kurtosis5.184974793
Mean192.11278
Median Absolute Deviation (MAD)31
Skewness2.539479865
Sum9605639
Variance161417.0102
MonotonicityNot monotonic
2025-11-02T20:39:13.767044image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13442
 
6.9%
52070
 
4.1%
21713
 
3.4%
1141663
 
3.3%
41650
 
3.3%
141647
 
3.3%
31546
 
3.1%
441458
 
2.9%
601242
 
2.5%
421210
 
2.4%
Other values (260)32359
64.7%
ValueCountFrequency (%)
13442
6.9%
21713
3.4%
31546
3.1%
41650
3.3%
52070
4.1%
ValueCountFrequency (%)
17235
 
< 0.1%
172015
< 0.1%
171926
0.1%
17143
 
< 0.1%
16916
 
< 0.1%
Distinct374
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size781.2 KiB
2025-11-02T20:39:14.190081image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length54
Median length37
Mean length11.94828
Min length2

Characters and Unicode

Total characters597414
Distinct characters66
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)< 0.1%

Sample

1st rowThe Lafayette
2nd rowJust The Big Room
3rd rowBunker Three
4th rowMusic Hall
5th rowSpiegeltent Palais Du Variete
ValueCountFrequency (%)
hall6813
 
6.7%
theatre6206
 
6.1%
the5991
 
5.9%
studio3202
 
3.1%
main2770
 
2.7%
room2733
 
2.7%
grand2487
 
2.4%
pleasance2446
 
2.4%
one1690
 
1.7%
mcewan1663
 
1.6%
Other values (408)65767
64.6%
2025-11-02T20:39:14.762639image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e68959
 
11.5%
53923
 
9.0%
a50713
 
8.5%
n34417
 
5.8%
l33614
 
5.6%
r33537
 
5.6%
t32708
 
5.5%
o31679
 
5.3%
i26626
 
4.5%
h18485
 
3.1%
Other values (56)212753
35.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)597414
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e68959
 
11.5%
53923
 
9.0%
a50713
 
8.5%
n34417
 
5.8%
l33614
 
5.6%
r33537
 
5.6%
t32708
 
5.5%
o31679
 
5.3%
i26626
 
4.5%
h18485
 
3.1%
Other values (56)212753
35.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)597414
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e68959
 
11.5%
53923
 
9.0%
a50713
 
8.5%
n34417
 
5.8%
l33614
 
5.6%
r33537
 
5.6%
t32708
 
5.5%
o31679
 
5.3%
i26626
 
4.5%
h18485
 
3.1%
Other values (56)212753
35.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)597414
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e68959
 
11.5%
53923
 
9.0%
a50713
 
8.5%
n34417
 
5.8%
l33614
 
5.6%
r33537
 
5.6%
t32708
 
5.5%
o31679
 
5.3%
i26626
 
4.5%
h18485
 
3.1%
Other values (56)212753
35.6%
Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size781.2 KiB
2025-11-02T20:39:14.922828image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length39
Median length3
Mean length3.8951
Min length3

Characters and Unicode

Total characters194755
Distinct characters41
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowWeb
2nd rowWeb
3rd rowWeb
4th rowWeb
5th rowWeb
ValueCountFrequency (%)
web44536
81.5%
counters1826
 
3.3%
phones1601
 
2.9%
half1126
 
2.1%
price1126
 
2.1%
hut1126
 
2.1%
583
 
1.1%
friends469
 
0.9%
customer366
 
0.7%
services366
 
0.7%
Other values (15)1532
 
2.8%
2025-11-02T20:39:15.209742image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e51911
26.7%
W44767
23.0%
b44536
22.9%
r4908
 
2.5%
s4769
 
2.4%
4657
 
2.4%
n4374
 
2.2%
o4092
 
2.1%
t3715
 
1.9%
u3497
 
1.8%
Other values (31)23529
12.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)194755
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e51911
26.7%
W44767
23.0%
b44536
22.9%
r4908
 
2.5%
s4769
 
2.4%
4657
 
2.4%
n4374
 
2.2%
o4092
 
2.1%
t3715
 
1.9%
u3497
 
1.8%
Other values (31)23529
12.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)194755
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e51911
26.7%
W44767
23.0%
b44536
22.9%
r4908
 
2.5%
s4769
 
2.4%
4657
 
2.4%
n4374
 
2.2%
o4092
 
2.1%
t3715
 
1.9%
u3497
 
1.8%
Other values (31)23529
12.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)194755
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e51911
26.7%
W44767
23.0%
b44536
22.9%
r4908
 
2.5%
s4769
 
2.4%
4657
 
2.4%
n4374
 
2.2%
o4092
 
2.1%
t3715
 
1.9%
u3497
 
1.8%
Other values (31)23529
12.1%